A Novel Weighted Spatial Smoothing DOA Estimation Algorithm for Coherent Signals
Jiaqiang Peng, Guimei Zheng, Qinyu Zhu · 2020
Weighted spatial smoothing algorithm is a powerful tool for estimating the direction of arrival(DOA) in a coherent signal scenario. Compared to spatial smoothing algorithm, the weighted spatial smoothing algorithm takes the cross-covariance between the subarrays into consideration, which greatly improved the utilization of the information received by the sensor array. However, the performance of the weighted spatial smoothing algorithm is greatly based on the weighting factor. And the conventional weighting factor is preestimated by some other methods, which is not easy to be applied into the practical scenarios. In this paper, we propose a novel weighted spatial smoothing algorithm, which digging deep into the information of each sub-matrix of the array received data covariance matrix, and exploit the conjugate of the sum of the diagonal elements of the sub-matrix as it's weighting factor, which can be obtained with the coming of the sub-matrix. As a result, the proposed algorithm reduced the computational complexity, enhanced the stability, and achieved a high estimation accuracy. The superiority of the proposed algorithm is validated by numerical simulations.